Stripe pattern image analysis device, stripe pattern image analysis method, and program thereof

ABSTRACT

Provided is a stripe pattern image analysis device by which a burden of an appraiser regarding a new charting point searching designation operation can be reduced. The device includes a charting point modification element obtaining or modifying a first point located on a first stripe pattern image displayed in a first window, and a second point which is corresponding to the first point and located on a second stripe pattern image displayed in a second window; a nonlinear coordinate transformation element transforming the first stripe pattern image using a nonlinear coordinate transformation so that a first coordinate of the first point in the first window matches a second coordinate of the second point in the second window; and a charting figure edit and display element displaying the first stripe pattern image, transformed by the nonlinear coordinate transformation element by use of the nonlinear coordinate transformation, in the first window.

TECHNICAL FIELD

The present invention relates to a stripe pattern image analysis device,a stripe pattern image analysis method and a program thereof whichsupport to judge whether stripe pattern images are different each other,and particularly relates to a stripe pattern image analysis device, astripe pattern image analysis method and a program thereof which supportto analyze two images of, for example, a fingerprint or a palm print(judge whether or not the two images are taken, for example, from thesame finger or palm).

BACKGROUND ART

Since a fingerprint, which is composed of a plurality of ridges in astripe pattern, has two remarkable features that the fingerprint isinvariable throughout life and the fingerprints of any two persons aredifferent each other, the fingerprint has been used as a means torecognize a person from the old days.

According to the analysis of the fingerprint, an examiner compares twofingerprint data, and analyzes visually whether features on thefingerprint ridges match each other. Then, the examiner judges that twofingerprints are identical each other, in the case that number of theridge features, which become paired out of two fingerprint data, becomesnot smaller than a predetermined number.

Here, the ridge feature of the fingerprint means an end point or abifurcation of a line which composes the stripe. The ridge featureswhich become paired out of two data (in this case, fingerprint data) arecalled corresponding ridge features.

In many cases, not only the ridge feature such as the end point or thebifurcation but also other detailed features of the ridges, for example,a short line (dot) or a sweat pore are used for the judgment onidentity. Accordingly, the ridge feature used for the judgment on theexistence of difference between the fingerprints includes not only theend point or the bifurcation but also another detailed feature of theridge.

In a trial, a document, which indicates a relation between authorizedcorresponding ridge features, is submitted together with two fingerprintphotographs and two fingerprint gray images which are arrangedadjacently. According to the trial in many countries, two fingerprintsare judged to be identical each other in the case that about 12corresponding ridge features are found out of the two fingerprint data.Details are described on 190 to 193 pages of non-patent document 1; “TheScience of Fingerprints-Classification and Uses (John Edgar Hoover, USDOJ, FBI; 1963)”.

In recent years, a fingerprint matching system using a computer becomesprevailing, and consequently documentary evidence for the trial is alsocreated by use of a computer in many cases. A function to edit anddisplay two fingerprints so that the corresponding ridge features may bedisplayed clearly is called to be the Charting Function and isprevailing in USA in particular.

According to the Charting Function, two fingerprints are displayedadjacently, that is, one is arranged on the left side and the other isarranged on the right side so that the judgment on the existence ofdifference may be carried out easily. The display method mentioned aboveis called to be a side by side display. A figure and a screen which aredisplayed with the side by side display method are called to be acharting figure and a charting screen respectively. Two correspondingpoints are called to be charting points. A line, which ties two chartingpoints, is also displayed in many cases. The line is called to be acharting line. The judgment on the existence of difference between thefingerprints is also called to be a fingerprint analysis.

The Charting Function, which is carried out semi-automatically by use ofan automatic matching function, has been realized already. According tothe semi-automatic Charting Function, it is unnecessary that theexaminer inputs information on all corresponding ridge features by amanual operation. The ridge features, which become corresponding, areextracted by the automatic matching function, and then the correspondingridge features are displayed automatically as the charting point. Theexaminer checks and modifies the corresponding ridge features which aredisplayed.

FIG. 10A and FIG. 10B show examples of the charting figures which aredisplayed by the charting function. FIG. 10A is the example of thecharting figure to make a relation between the corresponding chartingpoints clear through tying the charting points by the charting line andassigning the same number to the corresponding charting points. FIG. 10Bis the example of display which is obtained through carrying out alinear transformation (rotation and parallel movement) for one image(right side fingerprint) of the fingerprint data of the charting figureshown in FIG. 10A so that the corresponding charting points are arrangedalmost horizontally.

Here, a technical document, which is applied before the presentapplication, discloses a method to make the visual judgment on theexistence of difference easy, for example, through modifying an imagedistortion so that one fingerprint image may match the other fingerprintimage, and displaying two fingerprint images adjacently (for example,refer to patent document 1).

The patent document 1 mentioned above discloses a method to modify theimage distortion on the basis of a distance between corresponding ridgefeatures and a core of the fingerprint.

It is difficult to use the method mentioned above in the case thatcoordinates of the corresponding ridge features does not always matcheach other and there is no core of the fingerprint. The fingerprint withno core is, for example, an arched fingerprint or a latent fingerprint(partial fingerprint) whose core is not taken.

It is difficult to apply the modification method, which is disclosed inthe above-mentioned patent document 1, to modification of the image ofthe above-mentioned fingerprint.

Patent document 2 discloses a method to support the analysis throughmodifying image distortion of one image out of two images perfectly byuse of a large amount of corresponding points of the skeletons outputtedas a result of skeleton matching, and overlapping the one image with theother image.

It is impossible to use the method in the case that coordinates of thecorresponding ridge features do not always match each other, and theskeleton matching fails due to degraded quality of the image. Moreover,in the case that the method is applied to the latent fingerprint withlow quality, the examiner must input skeleton data by a manualoperation, and consequently, a work load of the examiner becomes severe.

Patent document 3 discloses an art to compare a plurality of images withease through making a display means display simultaneously the imageswhich photograph an eye in plural different states and include anidentical photographing area.

Patent document 4 discloses an art which enables to comparesimultaneously two different three-dimensional surface rendering imagesor the like, or to observe at once a state of three-dimensionaldistribution related to a plurality of different wall movementinformation.

THE PRECEDING TECHNICAL DOCUMENT

[Patent Document]

-   [Patent document 1] Japanese Patent Publication No. 2885787-   [Patent document 2] Japanese Patent Application Laid-Open No.    2004-078434-   [Patent document 3] Japanese Patent Application Laid-Open No.    1994-269413-   [Patent document 4] Japanese Patent Application Laid-Open No.    2009-28167

[Non-patent Document]

-   [Non-patent Document 1] Page 193 to 196 of “The Science of    Fingerprints Classification and Uses” (by John Edgar Hoover, US DOJ,    FBI; Rev. 12-84 and 1990)

DISCLOSURE OF INVENTION Problem to be Solved by the Invention

In the case that a device with the Charting Function fails in theautomatic matching due to quite low quality of the latent fingerprint,and consequently can not extract the corresponding ridge features, theexaminer must make all charting points corresponding to each other inthe fingerprint analysis. Therefore, there is a problem that a work loadof the examiner is heavy.

A usual procedure to make the charting points corresponding to eachother is as follows.

Step 1: The examiner compares two fingerprints and determines thecharting points which should be corresponding.

Step 2: The examiner designates a position of the determined ridgefeature on one fingerprint.

Step 3: The examiner designates a position of the determined ridgefeature on the other fingerprint.

Here, the designation of the position in Steps 2 and 3 is usuallycarried out by use of a pointing device such as a mouse and a tabletpen. However, the work load of the examiner becomes heavy if a distanceof the pointing device's moving in order to designate the position islong.

The present invention is conceived in consideration of the abovementioned situation. An object of the present invention is to provide astripe pattern image analysis device, a stripe pattern image analysismethod and a program thereof to be able to reduce the work load of theexaminer or the like which is generated in the operation of searchingand designating new charting points.

Means for Solving the Problem

In order to achieve the object, the present invention has the followingfeature.

<Stripe Pattern Image Analysis Device>

A stripe pattern image analysis device according to the presentinvention comprises:

a charting point modification means for obtaining or modifying a firstpoint located on a first stripe pattern image displayed in a firstwindow, and a second point which is corresponding to the first point andlocated on a second stripe pattern image displayed in a second window;

a nonlinear coordinate transformation means for transforming the firststripe pattern image by use of a nonlinear coordinate transformation sothat a first coordinate of the first point in the first window matches asecond coordinate of the second point in the second window; and

a charting figure edit and display means for displaying the first stripepattern image, transformed by the nonlinear coordinate transformationmeans by use of the nonlinear coordinate transformation, in the firstwindow.

<Stripe Pattern Image Analysis Device Method>

A stripe pattern image analysis method according to the presentinvention comprises:

carrying out a charting point modification for obtaining or modifying afirst point located on a first stripe pattern image displayed in a firstwindow, and a second point which is corresponding to the first point andlocated on a second stripe pattern image displayed in a second window;

carrying out a nonlinear coordinate transformation for transforming thefirst stripe pattern image by use of a nonlinear coordinatetransformation so that a first coordinate of the first point in thefirst window matches a second coordinate of the second point in thesecond window; and

carrying out a charting figure edit and display for displaying the firststripe pattern image, which is transformed by use of the nonlinearcoordinate transformation in the nonlinear coordinate transformation, inthe first window.

<Program>

A program according to the present invention makes a computer execute:

a charting point modification process to obtain or to modify one a firstpoint located on a first stripe pattern image displayed in a firstwindow and a second point which is corresponding to the first point andlocated on a second stripe pattern image displayed in a second window;

a nonlinear coordinate transformation process to transform the firststripe pattern image by use of a nonlinear coordinate transformation sothat a first coordinate of the first point in the first window matches asecond coordinate of the second point in the second window; and

a charting figure edit and display process to display the first stripepattern image, which is transformed by use of the nonlineartransformation in the nonlinear coordinate transformation process, inthe first window.

Effect of the Invention

According to the present invention, it is possible to reduce the workload of the examiner or the like which is generated in the operation ofsearching and designating new charting points.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 shows an example of a whole of configuration of a chartingsupport processing device 10 according to an exemplary embodiment.

FIG. 2 shows an example of a configuration of a charting support unit12.

FIG. 3 shows an example of an operation of the charting supportprocessing device 10.

FIG. 4A shows an example of a latent fingerprint which is used incharting.

FIG. 4B shows an example of an image of an inked fingerprint which isused in the charting.

FIG. 5 shows an example of side by side display of the latentfingerprint and the inked fingerprint which is not transformed.

FIG. 6 shows an example of the side by side display of the latentfingerprint and the inked fingerprint which is transformed by use of alinear transformation.

FIG. 7 shows an example of the side by side display of the latentfingerprint and the inked fingerprint which is transformed by use of anonlinear transformation.

FIG. 8 is a diagram for explaining an effect of an image transformation.

FIG. 9 is another diagram for explaining the effect of the imagetransformation.

FIG. 10A is a diagram (1) showing an example of the charting related tothe present invention.

FIG. 10B is a diagram (2) showing an example of the charting related tothe present invention.

FIG. 11 shows an example of false analysis.

FIG. 12 shows an example of the side by side display, which is displayedin the case of the false analysis and which displays the inkedfingerprint and the latent fingerprint transformed by use of the lineartransformation.

FIG. 13 shows an example of the side by side display of the inkedfingerprint and the latent fingerprint transformed by use of thenonlinear transformation which is displayed in the case of the falseanalysis.

FIG. 14 shows an example of a whole of configuration of a stripe patternimage analysis device 17 according to an exemplary embodiment.

DESCRIPTION OF CODES

-   -   10 Charting support processing device    -   11 Fingerprint image input unit    -   12 Charting support unit    -   13 Data input unit    -   14 Data display unit    -   15 Fingerprint image output unit    -   16 Hard copy device    -   17 Stripe pattern image analysis device    -   21 Data processing control unit    -   22 Data storage unit    -   23 Charting point modification unit    -   24 Linear coordinate transformation unit    -   25 Nonlinear coordinate transformation unit    -   26 Corresponding point coordinate table creation unit    -   27 Corresponding point coordinate retrieval unit    -   28 Charting figure edit and display unit

MOST PREFERRED MODE TO CARRY OUT THE INVENTION Outline of Stripe PatternImage Analysis Device According to Exemplary Embodiment of PresentInvention

FIG. 14 shows an outline of a stripe pattern image analysis device 17according to an exemplary embodiment of the present invention.

The stripe pattern image analysis device 17 according to the exemplaryembodiment of the present invention comprises:

a charting point modification means 23 for obtaining or modifying afirst point located on a first stripe pattern image displayed in a firstwindow, and a second point which is corresponding to the first point andlocated on a second stripe pattern image displayed in a second window;

a nonlinear coordinate transformation means 25 for transforming thefirst stripe pattern image by use of a nonlinear coordinatetransformation so that a first coordinate of the first point in thefirst window matches a second coordinate of the second point in thesecond window; and

a charting figure edit and display means 28 for displaying the firststripe pattern image transformed by the nonlinear coordinatetransformation means by use of the nonlinear coordinate transformation,in the first window.

According to the stripe pattern image analysis device 17 of theexemplary embodiment of the present invention, by virtue of theconfiguration mentioned above, it is possible to reduce a work load ofan examiner or the like which is generated in an operation of searchingand designating a new charting point. Hereinafter, the stripe patternimage analysis device 17 according to the exemplary embodiment of thepresent invention will be described in detail with reference to adrawing. Here, a charting support processing device 10 is exemplified inthe following description. However, the stripe pattern image analysisdevice 17 according to the exemplary embodiment is not limited to thecharting support processing device 10.

A First Exemplary Embodiment

<Example of Configuration of Charting Support Processing Device 10>

FIG. 1 shows an example of a configuration of the charting supportprocessing device 10.

The charting support processing device 10 includes a fingerprint imageinput unit 11, a charting support unit 12, a data input unit 13, a datadisplay unit 14, a fingerprint image output unit 15 and a hard copydevice 16.

The fingerprint image input unit 11 digitizes and obtains a fingerprintimage which is read, for example, by a sensor and a scanner. It may bepreferable that the fingerprint image input unit 11 obtains an image,which has been already digitized, as a file.

The charting support unit 12 has a charting function to support judgmenton identity of fingerprints in two fingerprint images which are providedby the fingerprint image input unit 11.

The data input unit 13, which is an input device called to be a pointingdevice such as a mouse and a tablet, obtains data such as position of apoint designated by an examiner, and an instruction of the examiner.

The data display unit 14, which is, for example, a monitor displaydevice or the like, displays charting data such as the fingerprintimage, a charting point and a charting line.

The fingerprint image output unit 15 outputs a transformed image whichis processed by the charting support unit 12, and provides an externalsystem, an external storage medium or the like with the outputted image.

The hard copy device 16, which is a printing device such as a printer,prints and outputs an analysis result (charting screen) or the like.

<Example of Configuration of Charting Support Unit 12>

FIG. 2 shows an example of a configuration of the charting support unit12.

The charting support unit 12 includes a data processing control unit 21,a data storage unit 22, the charting point modification unit 23, alinear coordinate transformation unit 24, the nonlinear coordinatetransformation unit 25, a corresponding point coordinate table creationunit 26, a corresponding point coordinate retrieval point 27 and thecharting figure edit and display unit 28.

The data processing control unit 21 controls each unit, which composesthe charting support unit 12, to send data and a message to another unitand to receive the data and the message from another unit.

The data storage unit 22 is, for example, RAM (Random Access Memory),and is used by each unit of the charting support unit 12 as a workingarea or the like. Moreover, each of the charting point modification unit23, the linear coordinate transformation unit 24, the nonlinearcoordinate transformation unit 25, the corresponding point coordinatetable creation unit 26, the corresponding point coordinate retrievalunit 27 and the charting figure edit and display unit 28 use the datastorage unit 22 as a working area.

The charting point modification unit 23 supports the examiner'sinputting and modifying work related to corresponding points (acorresponding point is called a charting point) on two images.

The linear coordinate transformation unit 24 determines a coordinatetransformation formula for minimizing difference (distance) between thecoordinates of the charting points which are defined on two imagesrespectively. The coordinate transformation formula is determined underthe condition of a linear transformation.

To determine the coordinate transformation formula is to find a lineartransformation formula for a whole of the image which makes a coordinateof a position of a charting point on one image close to a coordinate ofa position of the corresponding charting point on the other image.

The nonlinear coordinate transformation unit 25 determines a coordinatetransformation relation for matching two charting points which aredefined on two images respectively. The coordinate transformation cannotbe realized by the linear transformation. The nonlinear coordinatetransformation unit 25 determines an amount of transformation (amount ofmovement) of any pixel on one image according to the interpolationmethod by use of an amount of movement of a nearby charting point, and adistance from the pixel to the nearby charting point. The imagetransformation by use of the amount of transformation based on thenonlinear coordinate transformation can rectify an image distortion.

The corresponding point coordinate table creation unit 26 creates acorresponding point coordinate table which stores a relation ofcorrespondence between the coordinate of the pixel posterior to thenonlinear transformation, and the coordinate of the pixel prior to thenonlinear transformation.

The corresponding point coordinate table creation unit 26 registers areverse relation between the coordinate of the pixel prior to thenonlinear transformation, and the coordinate of the pixel posterior tothe nonlinear transformation in the corresponding point coordinatetable.

The corresponding point coordinate retrieval unit 27 searches for thecorresponding point coordinate table, and determines a coordinate of thepixel prior to the nonlinear transformation which is corresponding tothe coordinate of the pixel designated on the nonlinear transformationimage.

The charting figure edit and display unit 28 edits the relation ofcorrespondence between two fingerprint images so that the examiner mayunderstand easily the relation of correspondence between two fingerprintimages.

The charting figure edit and display unit 28 makes the data display unit14 display an edited image and a requested image such as the chartingdata on the basis of an examiner's instruction which is provided by thedata input unit 13.

<Operation of Charting Support Processing Device 10>

FIG. 3 shows an operation of a whole of the charting support unit 12which includes the fingerprint image input unit 11, the data input unit13, the data display unit 14 and the fingerprint image output unit 15.

First, the fingerprint image input unit 11 obtains fingerprint images(Step S101).

For example, the fingerprint image input unit 11 digitizes images whichare read by a scanner and obtains the digitalized image, or thefingerprint image input unit 11 obtains files of the fingerprint imageswhich have been digitalized already. FIG. 4A and FIG. 4B show an exampleof fingerprint images which the fingerprint image input unit 11 obtains.

FIG. 4A shows an example of an image of a latent fingerprint, and FIG.4B shows an example of an image of an inked fingerprint which iscorresponding to the latent fingerprint.

The latent fingerprint, which means a fingerprint left behind at a sceneof a crime, has low quality, and consequently automatic matching may beimpossible in many cases. On the other hand, the inked fingerprint,which is taken for registration, has high quality. The inked fingerprintwhich is taken for a criminal, investigation is called specifically arolled impression since the fingerprint is taken with making a fingerrotated so that a wide area of the fingerprint may be taken.

Here, two fingerprints, which are objects for judgment on identity, willbe described in the following. While both of the fingerprints may belatent fingerprints or inked fingerprints, it is usual that one out oftwo fingerprints is a latent fingerprint and the other is an inkedfingerprint. For the sake of convenience, it is assumed that one out oftwo fingerprints, which are the objects for checking identity, is alatent fingerprint, and the other is an inked fingerprint.

FIG. 4A and FIG. 4B or the like show an example of the fingerprintimages which are read by a sensor or a scanner and afterward isdigitalized. The examples of the fingerprint images are digitized withresolution of 500 dpi according to ANSI/NIST-ITL-1-2000 Data Format forthe Interchange of Fingerprint, Facial, & Scar Mark & Tattoo (SMT)Information which is standardized by American NIST (National Instituteof Standards and Technology). Here, the standardized document isdisclosed in NIST Special Publication 500-245 of ANSI/NIST-ITL 1-2000Revision of ANSI/NIST-CSL 1-1993 & ANSI/NIST-ITL 1a-1997 [retrieved atMar. 11, 2009], internet<URL:ftp://sequoyah.nist.gov/pub/nist_internal_reports/sp500-245-a16.pd.

Next, the charting figure edit and display unit 28 edits two fingerprintimages, which are provided by the fingerprint image input unit 11, foran initial display and makes the data display unit 14 display the editedfingerprints (Step S102).

FIG. 5 is an example of the fingerprint image displayed on the datadisplay unit 14. If there is no specific remark in this description, anyfigure included in the exemplary embodiment shows the latent fingerprinton the left side and the inked fingerprint on the right side of the sideby side display. Moreover, it is assumed that the object for thecoordinate transformation and the image transformation is the inkedfingerprint which is displayed on the right side.

Next, the data processing control unit 21 carries out a processaccording to an input instruction issued by the examiner.

The data processing control unit 21 judges whether an input instructionissued by the examiner is an end instruction or not (Step S103). In thecase that the input instruction is the end instruction (Yes in StepS103), the data processing control unit 21 ends the charting supportprocess (End).

On the other hand, in the case that the input instruction is not the endinstruction (No in Step S103), the data processing control unit 21judges whether an input instruction issued by the examiner is aninstruction for modifying charting points on the not-transformed image(Step S104).

In the case that the input instruction is the instruction for modifyingcharting points on the not-transformed image (Yes in Step S104), thecharting point modification unit 23 carries out a support process forobtainment or modification work related to charting points, and advancesthe operation towards Step S105 after completion of the process.

In the description of the exemplary embodiment, the charting supportprocessing device 10 carries out the linear transformation or thenonlinear transformation of the inked fingerprint shown on the rightside in FIG. 4B, so as to make it similar in shape to the latentfingerprint shown on the left side in FIG. 4A. The not-transformed imagemeans an image whose inked fingerprint remains as it is as thefingerprint on the input image, and for which the image transformationis not carried out. In an example of the side by side display shown inFIG. 5, an inked fingerprint on a right side image b is anot-transformed image O.

Inputting the charting points in FIG. 5 includes two steps ofdesignating a charting point 51 of the latent fingerprint anddesignating a charting point 52 of the inked fingerprint. It may bepreferable that inputting the charting points is carried out in areverse order, that is, the designation of the charting point 52 of theinked fingerprint is carried out at first, and afterward the designationof the charting point 51 of the latent fingerprint is carried out.

In FIG. 5, a center of a short line (short ridge) is a first chartingpoint. A small window which exists between the left image and the rightimage shows an enlarged view around each charting point of the leftimage and the right image.

The inked fingerprint image, which is not transformed and which isdisplayed in the right side window b in FIG. 5 or the like, means, inother word, an image whose position alignment for making the inkedfingerprint image corresponding to the latent fingerprint image is notcarried out. Accordingly, the inked fingerprint image which is nottransformed is not corresponding well to the latent fingerprint.Therefore, a position of the charting point 51 of the latent fingerprintin the display window, and a position of the charting point 52 of theinked fingerprint in the display window are different.

In order to explain a relation between the positions in two displaywindows, other charting points (bifurcations 53 and 54) are exemplified.A cursor mark 55 is placed (pointing) so that the cursor mark 55 mayindicate the charting point 53 in a left side display window a. Aposition indicated by a cursor mark 56 in the right side display windowb in FIG. 5 is identical to one of the cursor mark 55 in the left sidedisplay window a. A function to display one cursor at a position in onedisplay window, and the other cursor at the same position in the otherdisplay window is called double cursor function.

The cursor mark 56 is far from the charting point 54. If, for example,the position alignment of the image in the right side display window bto the image in the left side display window a can be carried outthrough transforming the image in the right side display window b, adistance between the two points becomes short apparently.

The charting support processing device 10 according to the exemplaryembodiment makes two points close through carrying out the coordinatetransformation by use of the coordinates of the charting points at atime when one or more than one pairs of charting points are inputted.

For example, when one pair of charting points is designated forinputting, the charting support processing device 10 moves the image inthe right side display window b in parallel so that the coordinate ofthe charting point in the right side display window b matches thecoordinate of the charting point in the left side display window a.

Moreover, when two pairs of charting points are designated forinputting, the charting support processing device 10 moves the image inthe right side display window b in parallel so that a central coordinateof the two charting points in the right side display window b matches acentral coordinate of the two charting points in the left side displaywindow a. Next, the charting support processing device 10 rotates theimage in the right side display window b so that an angle of a linebetween the two charting points in the right side display window bmatches an angle of a line between the two charting points in the leftside display window a.

Moreover, when more than two charting points are designated forinputting, the charting support processing device 10 carries out thelinear transformation of the image in the right side display window bwith a usual image transformation technology such as the Helmerttransformation mentioned later.

In the case that the image in the left side display window a, and theimage in the right side display window b which is transformed in theabove-mentioned way are displayed side by side, the points which arepointed by the double cursor become well corresponding each other. Inother words, for example, in the case that the examiner places thedouble cursor at a new charting point a on the image in the left sidedisplay window a, a distance between a double cursor point on the imagein the right side display window b, and the charting point on the imagein the right side display window b, which is corresponding with thecharting point a, becomes short.

As a result, the charting support processing device 10 can reduce anamount of movement of the cursor which the examiner moves at a time whenthe examiner designates the new charting point. In other words, when theexaminer places the double cursor at the charting point on the image inthe left side display window a, the charting support processing device10 focuses another cursor (move the cursor and make it effective) on apoint which is at the same position in the right side display window b(candidate point for the charting point on the image in the right sidedisplay window b). What is left for the examiner to do is to move thecursor from the candidate point to a true charting point. Accordingly,the charting support processing device 10 can reduce an amount of worksfor designating the charting point of the image in the right sidedisplay window b.

A combination of the image transformation and the double cursor reducesthe amount of works for designating new charting points, and furthermoremakes it easy to search new charting points. For example, when theexaminer designates the candidate point for a charting point on the leftside image by use of the cursor, a range for searching for a pointcorresponding to the candidate point is limited only to an area aroundthe point, which is designated by the double cursor, on the right sideimage.

It is ideal that an image transformation, which can make the chartingpoints on the left image and on the right image match the pointsdesignated by the double cursor, is realized. If the ideal imagetransformation is realized, it is furthermore easy to search anddesignate new charting points.

However, it is impossible to make the coordinates of the charting pointsof two images match with each other even if the image is transformed byuse of the linear transformation since the fingerprint image,especially, the latent fingerprint image is remarkable distorted.

In order to realize the image transformation which can make thecoordinates of the charting points of two images match with each other,the charting support processing device 10 according to the exemplaryembodiment carries out also the nonlinear image transformation which canrectify the image distortion.

<Image Transformation Process which is Carried Out in the Case ofCharting Point Modification on not-Transformed Image>

An image transformation process, which is carried out in the case thatan instruction issued by the examiner is, an instruction for modifyingthe charting point on the not-transformed image, includes threesub-steps as follows.

Sub step 1: linear coordinate transformation

Sub step 2: nonlinear coordinate transformation

Sub step 3: corresponding point coordinate table update

It is not mandatory that the charting support processing device 10carries out three sub-steps mentioned above in advance before modifyingthe charting point. But it is possible that the charting supportprocessing device 10 displays the requested image instantaneously in thecase that the examiner requests to display the linear transformed imageor the nonlinear transformed image, if the sub-steps are carried out inadvance.

<Sub Step 1: Linear Coordinate Transformation>

The linear coordinate transformation unit 24 determines a linearcoordinate transformation formula for minimizing difference (distance)in a distance between the charting points which are designated on twoimages respectively. The linear coordinate transformation means acoordinate transformation of a first degree equation which is applicableto a coordinate on a whole of the image. The linear transformation caninclude rotating the image, and moving the image in parallel, andexpanding and contracting the image.

Since an image which is transformed by use of the linear transformationdoes not include the modification of the image distortion, thetransformed image matches well with the image prior to thetransformation. Therefore, it is recognized commonly that thetransformed image can be used as a trial evidence with no problem.

According to the exemplary embodiment, the Helmert transformation isused as the linear transformation method. The Helmert transformation,which is adopted widely for processing a document such as a map, carriesout an approximate calculation of a transformation formula on the basisof a plurality of coordinates of corresponding points. Since the Helmerttransformation guarantees a similar type image posterior to thetransformation, the Helmert transformation is called also similar typetransformation. The Helmert transformation is easy to carry out aninverse transformation which calculates a coordinate prior to thetransformation from a coordinate posterior to the transformation.

The right side image b in FIG. 6 is an image L which is transformed byuse of the linear coordinate transformation formula. The image L is anexemplified image which is transformed by use of the coordinatetransformation based on only three charting points shown in FIG. 6.

A cursor mark 61 indicates a peak point of a skeleton (most inner ridge)of the fingerprint on the left side image a as shown in FIG. 6. The peakpoint is a new candidate for a charting point. A double cursor 62corresponding to the cursor mark 61 indicates a point which is far froma peak point of a skeleton of the right side image b by about 20 pixels(corresponding to actual distance of 1 millimeter). The correspondencebetween the left side image and the right side image in FIG. 6 isimproved remarkably in comparison with one in FIG. 5.

<Sub Step 2: Nonlinear Coordinate Transformation>

The nonlinear coordinate transformation unit 25 determines a coordinatetransformation method to make the coordinates of the charting points,which are designated on the two images respectively, match with eachother.

The nonlinear coordinate transformation unit 25 determines an amount oftransformation (amount of movement) of any pixel on one image accordingto the interpolation method by use of an amount of movement of a nearbycharting point, and a distance from the pixel to the nearby chartingpoint. The charting support processing device 10 can make thecoordinates of the charting points on two images matches with each otherand can make a nearby pixel distorted smoothly through carrying out theimage transformation by use of the amount of transformation. Since thecoordinate transformation is not linear (coordinate transformationformula cannot be expressed by a first degree equation), the coordinatetransformation is called nonlinear transformation.

The nonlinear coordinate transformation unit 25 according to theexemplary embodiment uses not the coordinate on the not-transformedimage O but the coordinate on the linear transformed image L in thenonlinear coordinate transformation process. Since the nonlinearcoordinate transformation according to the exemplary embodiment uses theamount of movement of the nearby charting point, the coordinate of thepixel which exists far from the charting point may not be transformedappropriately. The nonlinear coordinate transformation unit 25 canreduce the disadvantage through using the coordinate of the lineartransformed image L. As a result, the nonlinear coordinatetransformation unit 25 can make the image posterior to the nonlineartransformation more natural.

The nonlinear coordinate transformation according to the exemplaryembodiment can be realized by use of a publicly known technology whichis disclosed in Japanese Patent Application Laid-Open No. 1995-114649 orthe like. Japanese Patent Application Laid-Open No 1995-114649 disclosesa method to reduce distortion through designating a vector on a point onthe image, and deforming the image on the basis of the vector. In thecase of adopting the method described in Japanese Patent ApplicationLaid-Open No. 1995-114649, the nonlinear coordinate transformation unit25 sets that the vector originates at a position of a charting point ofthe inked fingerprint side, and terminates at a position of the chartingpoint of the latent fingerprint side which is corresponding to thecharting point on the inked fingerprint side. Then, by use of the methoddescribed in Japanese Patent Application Laid-Open No 1995-114649, thenonlinear coordinate transformation unit 25 determines a movement vectorof each pixel according to the interpolation method. The coordinate ofthe termination point of the movement vector which is determined withthe method mentioned above is a coordinate of pixel posterior to thenonlinear transformation.

Here, it may be preferable that the charting support processing device10 registers the coordinate of the pixel posterior to the nonlineartransformation correspondingly to the coordinate of the pixel prior tothe transformation in a coordinate transformation table. If thecoordinates are registered, the charting support processor 10 can searchthe coordinate of any pixel posterior to the transformationinstantaneously.

The right side image b in FIG. 7 is a nonlinear transformed image Nwhich is transformed by use of the coordinate transformation tablecreated as mentioned above.

The image N is an example of the image for which the coordinatetransformation is carried out by use of only three charting points asshown in FIG. 6 and FIG. 7. In FIG. 7, a cursor mark 71 indicates a peakpoint of a skeleton of the fingerprint of the left side image a. Thispeak point is a new candidate for a charting point. A double cursor 72corresponding to the cursor mark 71 indicates a point far by 6 pixels(corresponding to actual distance of 0.3 millimeter) from a peak pointof a skeleton of the fingerprint of the right side image. Thecorrespondence between the left side image and the right side image inFIG. 7 is improved furthermore in comparison with one in FIG. 6.

<Sub Step 3: Corresponding Point Coordinate Table Update>

The nonlinear coordinate transformation can not express thecorrespondence between the coordinate of the pixel posterior to thetransformation and the coordinate of the pixel prior to thetransformation with one formula as mentioned above. In this case, it iseffective to register the correspondence between the coordinate of thepixel image posterior to the transformation and the coordinate of thepixel mage prior to the transformation in the coordinate transformationtable in order to realize high speed coordinate transformation. A normalorder coordinate transformation table registers the coordinate of thepixel posterior to the transformation correspondently to the coordinateof the pixel prior to the transformation. A reverse order coordinatetransformation table registers the coordinate of the pixel prior to thetransformation correspondently to the coordinate of the pixel posteriorto the transformation in a reverse order. The corresponding pointcoordinate table includes these two tables. Here, the reverse ordercoordinate transformation table registers the coordinates in an orderreverse to the order of the coordinates registered in the normal ordercoordinate transformation table.

The corresponding point coordinate table creation unit 26 updates thecorresponding point coordinate table, which is related to all pixels, byuse of a coordinate of a charting point inputted at the point of time(“update” includes initial creation).

Next, the data processing control unit 21 judges whether an instructionissued by the examiner is an instruction for modifying charting pointson the linear transformed image (Step S106). In the case of theinstruction for modifying charting points on the linear transformedimage (Yes in Step S106), the charting point modification unit 23carries out a support process for obtainment or modification workrelated to charting points. When the process is completed, the operationadvances towards Step S107.

<Image Transformation Process Carried Out when Modifying Charting Pointon Linear Transformed Image>

An image transformation process, which is carried out in the case thatan instruction issued by the examiner is an instruction for modifyingcharting points on the linear transformed image, includes four sub-stepsas follows.

Sub step 1: calculation of coordinate of charting point onnot-transformed image

Sub step 2: linear coordinate transformation

Sub step 3: nonlinear coordinate transformation

Sub step 4: corresponding point coordinate table update

It is not mandatory that the charting support processing device 10carries out four sub-steps mentioned above in advance before modifyingthe charting point. But it is possible that the charting supportprocessing device 10 displays the requested image instantaneously in thecase that the examiner requests to display the linear transformed imageor the nonlinear transformed image, if the sub-steps are carried out inadvance.

<Sub Step 1: Calculation of Coordinate of Charting Point onnot-Transformed Image>

1: The linear coordinate transformation unit 24 calculates thecoordinate on the not-transformed image corresponding to the coordinateof the charting point which is modified or added on the lineartransformed image. The linear coordinate transformation unit 24calculates the coordinate by use of an inverse transformation formula ofthe linear coordinate transformation formula which is determined in thelatest linear coordinate transformation process.

<Sub Step 2: Linear Coordinate Transformation>

2: A linear coordinate transformation is the same as one in Step S105.However, the linear coordinate transformation unit 24 uses thecoordinate of the not-transformed image which is calculated in “1:calculation of coordinate of charting point on not-transformed image”mentioned above.

<Sub Step 3: Nonlinear Coordinate Transformation>

3: A nonlinear coordinate transformation is the same as one in StepS105. However, the nonlinear coordinate transformation unit 25 uses thecoordinate on the image posterior to the transformation which iscalculated in “2: linear coordinate transformation” mentioned above.

<Sub Step 4: Coordinate Corresponding Point Table Update>

4: A coordinate corresponding point table update process is the same asthe process in Step S105.

Next, the data processing control unit 21 judges whether an instructionissued by the examiner is an instruction for modifying charting pointson the nonlinear transformed image (Step S108). In the case of theinstruction for modifying charting points on the nonlinear transformedimage (Yes in Step S108), the charting point modification unit 23carries out a support process for obtainment or modification workrelated to charting points. When the process is completed, the operationadvances towards Step S109.

<Image Transformation Process Carried Out in the Case of Charting PointModification of Nonlinear Transformed Image>

An image transformation process, which is carried out in the case thatan instruction issued by the examiner is an instruction for modifyingcharting points on the nonlinear transformed image, includes foursub-steps as follows.

Sub step 1: calculation of coordinate of charting point onnot-transformed image

Sub step 2: linear coordinate transformation

Sub step 3: nonlinear coordinate transformation

Sub step 4: corresponding point coordinate table update

It is not mandatory that the charting support processing device 10carries out the four sub-steps mentioned above in advance beforemodifying the charting point. But it is possible that the chartingsupport processing device 10 displays the requested imageinstantaneously in the case that the examiner requests to display thelinear transformed image or the nonlinear transformed image, if thesub-steps are carried out in advance.

<Sub Step 1: Calculation of Coordinate of Charting Point onnot-Transformed Image>

1: The charting support processing device 10 calculates a coordinate onthe not-transformed image corresponding to the coordinate of thecharting point which is modified or added on the linear transformationimage. The calculation includes two procedures shown in the following.

First, the nonlinear coordinate transformation unit 25 searches anddetermines a coordinate of the charting point on the linear transformedimage by use of the reverse order coordinate transformation table of thecorresponding point coordinate table.

Next, the liner coordinate transformation unit 24 calculates acoordinate on the not-transformed image by use of the inversetransformation formula of the linear coordinate transformation formula,which is determined in the latest linear coordinate transformationprocess, on the basis of the coordinate of the charting point on thelinear transformed image.

<Sub Step 2: Linear Coordinate Transformation>

2: A linear coordinate transformation process is the same as the processin Step S107. However, the linear coordinate transformation unit 24 usesthe coordinate on the not-transformed image which is calculated in “1:calculation of coordinate of charting point on not-transformed image”.

<Sub Step 3: Nonlinear Coordinate Transformation>

3: A nonlinear coordinate transformation process is the same as processin Step S107. However, the nonlinear coordinate transformation unit 25uses the coordinate on the image posterior to the linear transformationwhich is calculated in “2: linear coordinate transformation”.

<Sub Step 4: Corresponding Point Coordinate Table Update>

4: A corresponding point coordinate table update process is the same asthe process in Step S107.

Next, the data processing control unit 21 judges whether an instructionissued by the examiner is an instruction for the image transformation,the image edit and display, outputting, or printing (Step S110). In thecase of the instruction for the image transformation, the image edit anddisplay, outputting, or printing, the operation advances towards StepS111.

First, according to the examiner's instruction which is provided by thedata input unit 13, the charting figure edit and display unit 28transforms a requested image if necessary. The charting figure edit anddisplay unit 28 makes the data display unit 15 display and print theedited image and the charting data.

The charting figure edit and display unit 28 transmits the transformedimage to an external device or provides an external storage medium orthe like with the transformed image as digital data.

<Work and Effect of Charting Support Processing Device 10>

FIG. 8 a and FIG. 8 b show images in which a character “A” is used as anexample created in order to explain a work and an effect of the chartingsupport processing device 10 according to the exemplary embodiment.

FIG. 8 a shows an original image, that is; a target image T. FIG. 8 bshows the not-transformed image O which is obtained by deforming thetarget T, that is, by rotating and moving in parallel the target T, andproviding with a trapezoid distortion and a nonlinear random distortion.

Even if there are only a few charting points between the not-transformedimage O and the target image T, the charting support processing device10 according to the exemplary embodiment can transform thenot-transformed image and make it similar to the target image Tefficiently.

According to the exemplary embodiment, the charting support processingdevice 10 carries out the image transformation by use of three chartingpoints which are indicated on each of the non-transformed image O andthe target image T. FIG. 8 c shows the image L for which the lineartransformation, that is, the Helmert transformation mentioned in theexemplary embodiment is carried out.

FIG. 8 d shows the image N posterior to the nonlinear transformation.FIG. 8 d shows that an area surrounded by three designated chartingpoints and its nearby area are transformed to become similar to thetarget image T.

However, according to the image shown in FIG. 8 d, an upper part and alower part of the character “A” are connected unnaturally, andconsequently the image becomes unnatural as a whole, since the upperpart of the character “A”, where is far from the charting point, is nottransformed appropriately.

Second Exemplary Embodiment

FIG. 9 a and FIG. 9 c, which are the same as FIG. 8 a and FIG. 8 crespectively, are shown again in order to make comparison with FIG. 9 eand FIG. 9 f easy.

According to a second exemplary embodiment, the linear coordinatetransformation of sub step 1 of Step S105, sub step 2 of Step S107 andsub step 2 of Step S109 in FIG. 3 are changed as follows.

In this sub step, the linear coordinate transformation unit 24 shown inFIG. 2 determines a linear coordinate transformation formula forminimizing difference (distance) between the coordinates of the chartingpoints which are defined on two images respectively. First, the linearcoordinate transformation unit 24 according to the second exemplaryembodiment carries out the Helmert transformation which is adopted inthe first exemplary embodiment.

Next, the linear coordinate transformation unit 24 tries to make acoordinate of the charting point, which is transformed with the Helmerttransformation, approximate to the coordinate of the charting point onthe target image (T) through expanding and contracting the coordinate ofthe charting point, which is transformed with the Helmerttransformation, in the horizontal direction and in the verticaldirection.

In the following formulas, n denotes number of the charting points, andPx (k) denotes a X-coordinate of a k′th charting point on thenon-transformed image, and Tx (k) denotes a X-coordinate of a k′thcharting point on the target image, and PxC denotes a X-coordinate ofthe center of gravity of all charting points on the non-transformedimage, and TxC denotes a X-coordinate of the center of gravity of allcharting points on the target image, and h denotes expansion ratio in aX-direction. The linear coordinate transformation unit 24 finds hthrough solving the following n formulas approximately.

$\begin{matrix}{\left( {{{Tx}(1)} - {TxC}} \right) = {h*\left( {{{Px}(1)} - {PxC}} \right)}} \\{\vdots \mspace{14mu} \vdots} \\{\left( {{{Tx}(n)} - {TxC}} \right) = {h*\left( {{{Px}(n)} - {PxC}} \right)}}\end{matrix}$

A coordinate transformation formula will be expressed in the nextformula. Here, Qx(k) means an X-coordinate posterior to the coordinatetransformation.

Qx(k)=Px(k)+h*(Px(k)−PxC)

Similarly, the linear coordinate transformation unit 24 obtains alsoexpansion ratio in the vertical direction and a coordinatetransformation formula.

While the process mentioned above (Helmert transformation, and expansionand contraction in the horizontal and in the vertical direction) isrealized with the Affine transformation, it is complicate to determine aparameter for the most suitable Affine transformation.

Next, the linear coordinate transformation unit 24 tries to make thecoordinate of the charting point, which is adjusted by the expansion andthe contraction in the horizontal and vertical directions, approximateto the coordinate of the target image (T) through adding simple skew(skew; slant distortion) modification to the coordinate of the chartingpoint.

In the following formulas, n denotes number of the charting points, and(Px(k) and Py(k)) denotes a coordinate of a k′th charting point on thenon-transformed image, and (Tx(k) and Ty(k)) denotes a coordinate of ak′th charting point on the target image, and v denotes a skewmodification coefficient in a Y-direction. The linear coordinatetransformation unit 24 finds v through solving the following n formulasapproximately.

$\begin{matrix}{{{{Px}(1)} - {{Ty}(1)}} = {v*{{Px}(1)}}} \\{\vdots \mspace{14mu} \vdots} \\{{{{Px}(n)} - {{Ty}(n)}} = {v*{{Px}(n)}}}\end{matrix}$

A coordinate transformation formula will be expressed in the nextformula. Here, Qy(k) denotes a Y-coordinate posterior to the coordinatetransformation.

Qy(k)=Py(k)+v*Px(k)

Similarly, the linear coordinate transformation unit 24 obtains alsoexpansion ratio in the vertical direction and a coordinatetransformation formula.

Since the image transformation including the skew modification is notthe equiangular transformation, the image transformation including theskew modification is not the linear transformation in the strict senseof the word. However, the transformation can be expressed by a firstdegree equation, and an image posterior to the transformation is almostnatural. Therefore, according to the exemplary embodiment, it is assumedthat the transformation is included in the linear transformation and iscarried out.

FIG. 9 e shows a linear transformed image L2 which is transformed by useof the linear coordinate transformation in the way mentioned above. Theimage shown in FIG. 9 e is natural in comparison with the lineartransformed image L shown in FIG. 9 c, and becomes more similar to thetarget image T shown in FIG. 9 a than the linear transformed image Laccording to the first exemplary embodiment.

FIG. 9 f shows a nonlinear coordinate transformed image N2 which isobtained through carrying out the nonlinear coordinate transformationprocess by use of the coordinate shown in FIG. 9 e, and transforming theimage by use of the result of the nonlinear coordinate transformation.The image is natural in comparison with the nonlinear transformed imageN shown in FIG. 8 d, and becomes more similar to the target image Tshown in FIG. 9 a.

It may be preferable that the linear coordinate transformation unit 24according to another exemplary embodiment adds trapezoid distortionmodification as the linear coordinate transformation which can beexpressed by a first degree equation.

Work and Effect of Second Exemplary Embodiment

FIG. 11 shows an example of the charting figures causing a falseanalysis.

The examiner designates 14 charting points shown in FIG. 11, and judgedthat the fingerprints are identical with each other since eachcorresponding charting points are coincident with each other, andfinally the judgment resulted in the false analysis.

The nonlinear transformed image, which the charting support processingdevice 10 according to the exemplary embodiment outputs, is useful forpreventing the false analysis.

FIG. 12 shows an image which is obtained through carrying out the linearimage transformation process by use of 6 charting points, which arepositioned on the upper side, out of 14 charting points designated bythe examiner, and which is displayed side by side together with thelatent fingerprint image. Even if these two images are compared, theridges which are different with each other in a shape can not be foundeasily.

FIG. 13 shows an image which is obtained through carrying out thenonlinear image transformation by use of the same 6 charting points, andwhich is displayed side by side together with the latent fingerprintimage. Comparing two images, it is found that width of the ridge in alower part of an area 131 becomes wider than one in an upper part of thearea 131 and the width of the ridge in the upper part of the area 131extremely narrow, and consequently the image becomes unnatural.

While the examiner, who is influenced by prejudice that the latentfingerprint is distorted remarkably, does not sense difference betweenthe two images when the examiner watches FIG. 12, the examiner sensesvisually remarkable difference when comparing two images in FIG. 13. Asa result, the examiner analyzes the fingerprint carefully, andconsequently it is possible to prevent the false analysis.

As mentioned above, since the charting support processing device 10 cancarry out the nonlinear image transformation which outputs quite naturalimages even in the case of using small number of the charting pointswhich are inputted manually, the charting support processing device 10according to the exemplary embodiment is effective for supporting theanalysis work.

Here, the exemplary embodiment mentioned above is the preferredexemplary embodiment according to the present invention, and the scopeof the present invention is not limited to only the above-mentionedexemplary embodiment. Various changes in form and details can be madetherein without departing from the spirit and scope of the presentinvention.

For example, while the fingerprint image is exemplified according to theabove-mentioned embodiment, the present invention is also applicable toan apparatus or the like for analyzing a palm print or the like whichhas a pattern similar to the finger print.

An operator of the charting support processing device 10 according tothe present invention is not limited to the examiner. It is apparentthat a person other than an expert on the analysis can also operate thecharting support processing device 10.

The control process of each unit which composes the charting supportprocessing device 10 can be carried out by use of hardware, software ora combination of the hardware and the software.

In the case that the processes are carried out by use of software, it ispossible to install a program, which records a sequence of theprocesses, in a memory of a computer which is equipped with a dedicatedhardware, and to execute the program. For example, it is possible torecord the program beforehand in a hard disk or ROM (Read Only Memory)which is recording media. Or, it is possible to store (record) theprogram in a removable recording medium temporarily or permanently. Itis possible to provide the removable recording medium as so-calledpackaged software. Here, a floppy (registered trademark) disk, CD-ROM(Compact Disc Read Only Memory), a MO (Magneto optical) disk, DVD(Digital Versatile Disc), a magnetic disk and a semiconductor memory areexemplified as the removable recording medium.

Here, the program is installed in the computer from the removablerecording medium mentioned above. Or, the program is transferred from adownload site to the computer through a wireless network or a wirednetwork.

While the charting support processing device 10 according to theexemplary embodiment carries out the processes mentioned abovesequentially, the operation of the charting support processing device 10is not limited to the sequential operation. That is, it is also possiblethat the charting support processing device 10 is configured so that thecharting support processing device 10 may carry out the processessimultaneously or separately on the basis of processing capability ofthe device which carries out the processes, or on the basis ofnecessity.

The present invention is applicable to a device which supports toanalyze two images (judgment on existence of difference) such as thefingerprint and the palm print.

This application is based upon and claims the benefit of priority fromJapanese Patent Application No. 2009-074501, filed on Mar. 25, 2009, thedisclosure of which is incorporated herein in its entirety by reference.

1. A stripe pattern image analysis device, comprising: a charting pointmodification unit which obtains or modifies a first point located on afirst stripe pattern image displayed in a first window, and a secondpoint which is corresponding to the first point and located on a secondstripe pattern image displayed in a second window; a nonlinearcoordinate transformation unit which transforms the first stripe patternimage by use of a nonlinear coordinate transformation so that a firstcoordinate of the first point in the first window matches a secondcoordinate of the second point in the second window; and a chartingfigure edit and display unit which displays the first stripe patternimage transformed by the nonlinear coordinate transformation unit by useof the nonlinear coordinate transformation, in the first window.
 2. Thestripe pattern image analysis device according to claim 1, furthercomprising: a linear coordinate transformation unit which carries out alinear transformation of the first stripe pattern image so that thefirst coordinate and the second coordinate are approximate, wherein thenonlinear coordinate transformation unit carries out the nonlineartransformation of the first stripe pattern image which is transformed bythe linear coordinate transformation unit.
 3. The stripe pattern imageanalysis device according to claim 2, wherein the linear coordinatetransformation unit carries out the linear transformation of the firststripe pattern image through carrying out the Helmert transformation,modification to expand or contract the first stripe pattern image in thehorizontal direction or in the vertical direction, and skewmodification.
 4. The stripe pattern image analysis device according toclaim 3, wherein the charting point modification unit comprises: adouble cursor unit which, in the case that a cursor is moved to acoordinate of a candidate for one point in one window out of the firstwindow and the second window, makes another cursor indicated at the samecoordinate in the other window.
 5. A stripe pattern image analysismethod, comprising: carrying out a charting point modification forobtaining or modifying a first point located on a first stripe patternimage displayed in a first window, and a second point which iscorresponding to the first point and located on a second stripe patternimage displayed in a second window; carrying out a nonlinear coordinatetransformation for transforming the first stripe pattern image by use ofa nonlinear coordinate transformation so that a first coordinate of thefirst point in the first window matches a second coordinate of thesecond point in the second window; and carrying out a charting figureedit and display for displaying the first stripe pattern image, which istransformed by use of the nonlinear coordinate transformation in thenonlinear coordinate transformation, in the first window.
 6. The stripepattern image analysis method according to claim 5, comprising: carryingout a linear coordinate transformation for carrying out a lineartransformation of the first stripe pattern image so that the firstcoordinate and the second coordinate are approximate; and carrying outthe nonlinear coordinate transformation for transforming the firststripe pattern image, which is transformed by use of the lineartransformation in the linear coordinate transformation, by use of thenonlinear transformation.
 7. The stripe pattern image analysis methodaccording to claim 6, comprising: carrying out the linear coordinatetransformation for carrying out the linear transformation of the firststripe pattern image through carrying out the Helmert transformation,modification to expand or contract the first stripe pattern image in thehorizontal direction or in the vertical direction, and skewmodification.
 8. A non-transient computer readable media on which aprogram is stored wherein the program makes a computer execute: acharting point modification process to input or to modify a first pointlocated in a first stripe pattern image displayed in a first window anda second point which is corresponding to the first point and located ona second stripe pattern image displayed in a second window; a nonlinearcoordinate transformation process to transform the first stripe patternimage by use of a nonlinear coordinate transformation so that a firstcoordinate of the first point in the first window matches a secondcoordinate of the second point in the second window; and a chartingfigure edit and display process to display the first stripe patternimage, which is transformed by use of the nonlinear transformation inthe nonlinear coordinate transformation process, in the first window. 9.The non-transient computer readable media according to claim 8, on whichthe program is stored wherein the program makes the computer execute: alinear coordinate transformation process to carry out a lineartransformation of the first stripe pattern image so that the firstcoordinate and the second coordinate are approximate; and the nonlinearcoordinate transformation process to carry out a nonlineartransformation of the first stripe pattern image transformed by use ofthe linear transformation in the linear coordinate transformationprocess.
 10. The non-transient computer readable media according toclaim 9, on which the program is stored wherein the program makes thecomputer execute: the linear coordinate transformation process to carryout the linear transformation of the first stripe pattern image throughcarrying out the Helmert transformation, modification to expand orcontract the first stripe pattern image in the horizontal direction orin the vertical direction, and skew modification.